This model is a fine-tuned version of Qwen/Qwen2.5-1.5B on the polyalign_dist_sft_train dataset. It achieves the following results on the evaluation set:

Loss: 1.7217

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 6
gradient_accumulation_steps: 8
total_train_batch_size: 48
total_eval_batch_size: 6
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.57.6
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

saiteja33/qwen2.5-1.5B-sample-dist-sft-en-final

polyalign

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

saiteja33/
qwen2.5-1.5B-sample-dist-sft-en-final